3 papers
cs.AI2024
Explaining Reinforcement Learning: A Counterfactual Shapley Values Approach
Yiwei Shi, Qi Zhang, Kevin McAreavey +1
This paper introduces a novel approach Counterfactual Shapley Values (CSV), which enhances explainability in reinforcement learning (RL) by integrating counterfactual analysis with…
cs.HC2024
A qualitative field study on explainable AI for lay users subjected to AI cyberattacks
Kevin McAreavey, Weiru Liu, Kim Bauters +7
In this paper we present results from a qualitative field study on explainable AI (XAI) for lay users (n = 18) who were subjected to AI cyberattacks. The study was based on a custo…
cs.AI2023
Modifications of the Miller definition of contrastive (counterfactual) explanations
Kevin McAreavey, Weiru Liu
Miller recently proposed a definition of contrastive (counterfactual) explanations based on the well-known Halpern-Pearl (HP) definitions of causes and (non-contrastive) explanatio…